Medical Physics

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Showing new listings for Tuesday, 3 June 2025

New submissions (showing 5 of 5 entries)

[1] arXiv:2506.00006 [pdf, html, other]

Title: Active Eye Lens Dosimetry With Dosepix: Influence of Measurement Position and Lead Glass Shielding

Leonie Ullmann, Florian Beißer, Rolf Behrens, Stefan Funk, Gerhard Hilgers, Oliver Hupe, Jürgen Roth, Tom Tröltzsch, Hayo Zutz, Thilo Michel

Comments: This work has been submitted to the IEEE for possible publication. 9 pages, 9 figures

Subjects: Medical Physics (physics.med-ph)

In this work, the effect of the measurement position on measurements of $H_\text{p}(3)$ of a new active eye lens dosemeter prototype based on the Dosepix detector is examined. A comparison between measuring directly in front of the eye and measuring at the side of the head of an Alderson phantom showed no significant influence on the resulting $H_\text{p}(3)$ for different radiation qualities and angles. In addition, to account for the absorption effect of radiation safety glasses, pieces of lead glass were attached to the front and side of the dosemeter. Corresponding effects and consequences for radiation protection measurements have been investigated by using a human like Alderson head phantom as well as thermoluminescent dosemeters (TLDs) and the active eye lens dosemeter prototype. For specific angles, the radiation was able to bypass the radiation safety glasses and lead glass pieces, leading to an increase in the measured $H_\text{p}(3)$. Compared to TLDs behind radiation safety glasses, measurements with the lead glass shielded prototype resulted in lower values for $H_\text{p}(3)$. Furthermore, the results did not reproduce previous findings where larger dose values were found for Dosepix behind lead glass pieces than for the TLDs behind radiation safety glasses. A possible reason might be that the dimensions of the lead glass pieces are not representative of the radiation safety glasses in front of the eye but, ultimately, it is not yet clear what the main reason for the deviation is. Therefore, it is advisable to test the same methodology in future investigations with other eyewear models and lead glass pieces to investigate whether similar behaviors occur.

[2] arXiv:2506.00029 [pdf, other]

Title: Characterization of atomization and delivery efficiency of exogenous surfactant in preterm infant lungs using an ex vivo respiratory model

Ghalia Kaouane, Jean-François Berret, Yannick Cremillieux, Noël Pinaud, Fanny Munsch, Bei Zhang, Michael Fayon, Rémy Gérard, Eric Dumas De La Roque, Sophie Perinel-Ragey, Lara Leclerc, Jérémie Pourchez

Comments: 18 pages 12 figures

Subjects: Medical Physics (physics.med-ph); Materials Science (cond-mat.mtrl-sci)

Administration of pulmonary surfactant is crucial for the treatment of respiratory distress syndrome (RDS) in preterm infants. The aim of this study is to evaluate the potential of Curosurf atomization via the Endosurf device, a recently developed spray technology, as a promising approach for surfactant delivery in infants with RDS. A comprehensive analysis was performed to evaluate the physicochemical properties of atomized Curosurf, including its surface tension and rheology. The size distribution of Curosurf vesicles was also investigated. An ex vivo respiratory model based on rabbit lungs breathing through an instrumented hypobaric chamber representing the thorax of a preterm infant was developed to provide proof of concept for regional aerosol deposition of atomized Curosurf. The atomization of Curosurf with the innovative Endosurf device did not significantly alter surface tension, but reduced vesicle size and promoted homogeneous distribution of Curosurf in the lungs. Rheological measurements showed the viscoelastic complexity of atomized Curosurf. This preliminary study confirmed the promising potential of Curosurf atomization via the Endosurf device for the distribution of surfactant in the lungs of infants with RDS. These advances could help to improve the treatment of RDS in preterm infants and offer new perspectives for healthcare professionals and affected families.

[3] arXiv:2506.00626 [pdf, other]

Title: Helmet ultrasound for brain imaging in post-hemicraniectomy patients

Yang Zhang, Karteekeya Sastry, Iyla Rossi, Joshua Olick-Gibson, Jonathan J. Russin, Charles Y. Liu, Lihong V. Wang

Subjects: Medical Physics (physics.med-ph); Signal Processing (eess.SP)

Noninvasive imaging deep into the adult brain at submillimeter and millisecond scales remains a challenge in medical imaging. Here, we report a helmet based ultrasound brain imager built from a customized helmet, a scanned ultrasound array, and three dimensional printing for real time imaging of human brain anatomical and functional information. Through its application to post hemicraniectomy patients in a sitting position, we achieved volumetric brain tissue structural, vascular, and blood flow images at centimeter scale depths with submillimeter and millisecond spatiotemporal resolutions. We also demonstrated the system capability to track cerebral blood flow over repeated imaging sessions, including during motion prone conditions. Our brain imager circumvents the skull and bridges the gap between high resolution human brain imaging and wearable convenience. This imager may serve as a platform for further investigations into human brain dynamics in post hemicraniectomy patients and offer insights into the brain that could surpass those obtained from non human primate studies.

[4] arXiv:2506.01572 [pdf, other]

Title: Advanced Nanostructured Topical Therapeutics for Psoriasis: Strategic Synthesis, Multimodal Characterization, and Preliminary Pharmacodynamic Profiling

Iqra Yousaf, Aqsa Yousaf

Comments: 24 pages

Subjects: Medical Physics (physics.med-ph); Artificial Intelligence (cs.AI); Biological Physics (physics.bio-ph)

Psoriasis is a long-term inflammatory skin disease that remains difficult to treat. In this study, we developed a new topical treatment by combining metal oxide nanoparticles: cerium oxide (CeO2), zinc oxide (ZnO), and silver (Ag), with natural plant extracts in a gel made from fish collagen and agar. The nanoparticles were characterized using UV-Vis spectroscopy, dynamic light scattering (DLS), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM), showing good stability and a uniform particle size distribution (ZnO averaged 66 nm).
To enhance therapeutic potential, the gel was enriched with plant-derived antioxidants from bitter melon, ginger, and neem. This formulation was tested on an animal model of psoriasis. The treated group exhibited faster wound healing and reduced inflammation compared to both placebo and untreated groups, with statistically significant results (p < 0.01 to p < 0.001) observed from Day 3, becoming more pronounced by Day 14.
These results indicate that the combination of nanoparticles with plant-based components in a topical gel may provide a promising new approach to psoriasis treatment. Further studies are recommended to evaluate long-term safety and therapeutic effectiveness.

[5] arXiv:2506.01878 [pdf, html, other]

Title: Monte Carlo Simulation and Dosimetric Analysis of Gold Nanoparticles (AuNPs) in Breast Tissue

Pedro Teles, Catarina Dias, João H. Belo, Célia Sousa, Paula Boaventura, Isabel Bravo, João Santos, Marissa Rylander

Subjects: Medical Physics (physics.med-ph); Data Analysis, Statistics and Probability (physics.data-an)

Precise radiation delivery is critical for effective radiotherapy, and gold nanoparticles (AuNPs) have emerged as promising tools to enhance local dose deposition while sparing the surrounding healthy tissue. In this study, the PENELOPE Monte Carlo code was used to investigate the dosimetry of AuNPs under different conditions and models. The Dose Enhancement Ratio (DER) was studied in water and breast tissue with spherical shapes and in agreement with previously published results. To further analyse the physical interactions of the particles around the AuNP, a Phase Space File (PSF) in a volume around the AuNPs was created. This showed that larger AuNPs lead to increased doses, as expected, yielding DER values exceeding 100 times. Finally, results reveal that in the volume surrounding the AuNP, 80% of emitted electrons originate from photoelectric absorption, leading to Auger electron emission cascades which were analysed in detail. It was also possible to establish a direct relation between number of secondaries and the particle volumes. The Local Effect Model (LEM) was used to determine sur- vival curves in AuNPs of different sizes at different gold concentrations. The last part of this work consisted in analysing a distribution of AuNPs within a flattened cell typical of clonogenic assays where a log-normal distribution of dose was observed. This led to the development of a new, mechanistic, Local Effect Model which, if further validated, can have further applications in-vitro and in-silico.

Cross submissions (showing 2 of 2 entries)

[6] arXiv:2506.00293 (cross-list from cond-mat.mtrl-sci) [pdf, other]

Title: Influence of X-ray Irradiation on the Magnetic and Structural Properties of Gadolinium Silicide Nanoparticles for Self-Regulating Hyperthermia

Samantha E. Smith, Santiago Bermudez, Pavan Chaitanya, Zoe Boekelheide, Jessika Rojas Marin, Ravi L. Hadimani

Subjects: Materials Science (cond-mat.mtrl-sci); Medical Physics (physics.med-ph)

Magnetic hyperthermia treatment (MHT) utilizes heat generated from magnetic nanoparticles (MNPs) under an alternating magnetic field (AMF) for therapeutic applications. Gadolinium silicide (Gd5Si4) has emerged as a promising MHT candidate due to its self-regulating heating properties and potential biocompatibility. However, the impact of high-dose X-ray irradiation on its magnetic behavior remains uncertain. This study examines Gd5Si4 nanoparticles exposed to 36 and 72 kGy X-ray irradiation at a high-dose rate (120 Gy/min). While X-ray diffraction, scanning electron microscopy, and energy dispersive spectroscopy confirm no structural or compositional changes, transmission electron microscopy reveals localized lattice distortions, along with observable changes in magnetic properties, as evidenced in magnetization vs. temperature and hysteresis measurements. Despite this, magnetocaloric properties and specific loss power (SLP) remain unaffected. Our findings confirm the stability of Gd5Si4 under high-dose X-ray irradiation, supporting its potential for radiotherapy (RT) and magnetocaloric cooling in deep-space applications.

[7] arXiv:2506.01105 (cross-list from math.NA) [pdf, html, other]

Title: A Positivity-Preserving Finite Element Framework for Accurate Dose Computation in Proton Therapy

Ben S. Ashby, Abdalaziz Hamdan, Tristan Pryer

Comments: 21 pages, 11 figures

Subjects: Numerical Analysis (math.NA); Medical Physics (physics.med-ph)

We present a stabilised finite element method for modelling proton transport in tissue, incorporating both inelastic energy loss and elastic angular scattering. A key innovation is a positivity-preserving formulation that guarantees non-negative fluence and dose, even on coarse meshes. This enables reliable computation of clinically relevant quantities for treatment planning. We derive a priori error estimates demonstrating optimal convergence rates and validate the method through numerical benchmarks. The proposed framework provides a robust, accurate and efficient tool for advancing proton beam therapy.

Replacement submissions (showing 3 of 3 entries)

[8] arXiv:2412.08499 (replaced) [pdf, html, other]

Title: Scattering polarimetry enables correlative nerve fiber imaging and multimodal analysis

Franca auf der Heiden, Markus Axer, Katrin Amunts, Miriam Menzel

Comments: 28 pages, 7 figures, all study data are available on this https URL

Journal-ref: Sci Rep 15, 18493 (2025)

Subjects: Medical Physics (physics.med-ph)

Mapping the intricate network of nerve fibers is crucial for understanding brain function. Three-Dimensional Polarized Light Imaging (3D-PLI) and Computational Scattered Light Imaging (ComSLI) map dense nerve fibers in brain sections with micrometer resolution using visible light. 3D-PLI reconstructs 3D-fiber orientations, while ComSLI disentangles multiple directions per pixel. So far, these imaging techniques have been realized in separate setups. A combination within a single device would facilitate faster measurements, pixelwise mapping, cross-validation of fiber orientations, and leverage the advantages of each technique while mitigating their limitations. Here, we introduce the Scattering Polarimeter, a microscope that facilitates correlative large-area scans by integrating 3D-PLI and ComSLI measurements into a single system. Based on a Mueller polarimeter, it incorporates variable retarders and a large-area light source for direct and oblique illumination, enabling combined 3D-PLI and ComSLI measurements. Applied to human and vervet monkey brain sections, the Scattering Polarimeter generates results comparable to state-of-the-art 3D-PLI and ComSLI setups and creates a multimodal fiber direction map, integrating the robust fiber orientations obtained from 3D-PLI with fiber crossings from ComSLI. Furthermore, we discuss applications of the Scattering Polarimeter for unprecedented correlative and multimodal brain imaging.

[9] arXiv:2505.12494 (replaced) [pdf, html, other]

Title: SMURF: Scalable method for unsupervised reconstruction of flow in 4D flow MRI

Atharva Hans, Abhishek Singh, Pavlos Vlachos, Ilias Bilionis

Subjects: Medical Physics (physics.med-ph)

We introduce SMURF, a scalable and unsupervised machine learning method for simultaneously segmenting vascular geometries and reconstructing velocity fields from 4D flow MRI data. SMURF models geometry and velocity fields using multilayer perceptron-based functions incorporating Fourier feature embeddings and random weight factorization to accelerate convergence. A measurement model connects these fields to the observed image magnitude and phase data. Maximum likelihood estimation and subsampling enable SMURF to process high-dimensional datasets efficiently. Evaluations on synthetic, in vitro, and in vivo datasets demonstrate SMURF's performance. On synthetic internal carotid artery aneurysm data derived from CFD, SMURF achieves a quarter-voxel segmentation accuracy across noise levels of up to 50%, outperforming the state-of-the-art segmentation method by up to double the accuracy. In an in vitro experiment on Poiseuille flow, SMURF reduces velocity reconstruction RMSE by approximately 34% compared to raw measurements. In in vivo internal carotid artery aneurysm data, SMURF attains nearly half-voxel segmentation accuracy relative to expert annotations and decreases median velocity divergence residuals by about 31%, with a 27% reduction in the interquartile range. These results indicate that SMURF is robust to noise, preserves flow structure, and identifies patient-specific morphological features. SMURF advances 4D flow MRI accuracy, potentially enhancing the diagnostic utility of 4D flow MRI in clinical applications.

[10] arXiv:2412.03318 (replaced) [pdf, html, other]

Title: Domain-Agnostic Stroke Lesion Segmentation Using Physics-Constrained Synthetic Data

Liam Chalcroft, Jenny Crinion, Cathy J. Price, John Ashburner

Subjects: Image and Video Processing (eess.IV); Computer Vision and Pattern Recognition (cs.CV); Medical Physics (physics.med-ph)

Segmenting stroke lesions in MRI is challenging due to diverse acquisition protocols that limit model generalisability. In this work, we introduce two physics-constrained approaches to generate synthetic quantitative MRI (qMRI) images that improve segmentation robustness across heterogeneous domains. Our first method, $\texttt{qATLAS}$, trains a neural network to estimate qMRI maps from standard MPRAGE images, enabling the simulation of varied MRI sequences with realistic tissue contrasts. The second method, $\texttt{qSynth}$, synthesises qMRI maps directly from tissue labels using label-conditioned Gaussian mixture models, ensuring physical plausibility. Extensive experiments on multiple out-of-domain datasets show that both methods outperform a baseline UNet, with $\texttt{qSynth}$ notably surpassing previous synthetic data approaches. These results highlight the promise of integrating MRI physics into synthetic data generation for robust, generalisable stroke lesion segmentation. Code is available at this https URL